P. K. Upadhyay, Nadia Mohamed Kunhi, Y. Gupta, Shaik Ishraq Ahamed, Jidhin Das
{"title":"Intelligent Energy Management System along with Solar-Wind Hybrid Power Source","authors":"P. K. Upadhyay, Nadia Mohamed Kunhi, Y. Gupta, Shaik Ishraq Ahamed, Jidhin Das","doi":"10.1109/Confluence47617.2020.9057824","DOIUrl":null,"url":null,"abstract":"Energy management is a vast subject of major significance and complexity. It entails in electing among the integrated set of sources to generate electrical energy that supplies to a set of loads by diminishing losses and expenses. The utilization of sources and consumption rate of loads are coherent, well-integrated and magnitude of the system, the optimal usage of sources must be performed in real-time to avoid power outage. With an increase in demands, there is an increase in improved productivity, which causes a reduction in greenhouse emissions and energy costs that are motivations for organizations to capitalize and implement new energy efficiency technologies and management strategies. This work aims to propose a system which can self-regulate a combined set of power sources namely green energy i.e., Solar-Wind Hybrid System and main grid, and loads organized as a unified group of individual systems, called micro-grid, to augment several measures such as cost-effectiveness and energy efficiency. This prototype is based on the multi-agent automated systems. These micro-grids, individually modelled as a self-directed entity, can interact and make its own decision giving the best outcome.","PeriodicalId":180005,"journal":{"name":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 10th International Conference on Cloud Computing, Data Science & Engineering (Confluence)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/Confluence47617.2020.9057824","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Energy management is a vast subject of major significance and complexity. It entails in electing among the integrated set of sources to generate electrical energy that supplies to a set of loads by diminishing losses and expenses. The utilization of sources and consumption rate of loads are coherent, well-integrated and magnitude of the system, the optimal usage of sources must be performed in real-time to avoid power outage. With an increase in demands, there is an increase in improved productivity, which causes a reduction in greenhouse emissions and energy costs that are motivations for organizations to capitalize and implement new energy efficiency technologies and management strategies. This work aims to propose a system which can self-regulate a combined set of power sources namely green energy i.e., Solar-Wind Hybrid System and main grid, and loads organized as a unified group of individual systems, called micro-grid, to augment several measures such as cost-effectiveness and energy efficiency. This prototype is based on the multi-agent automated systems. These micro-grids, individually modelled as a self-directed entity, can interact and make its own decision giving the best outcome.